pith:OUK2IEVM
CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models
CodeGraphVLP pairs a persistent semantic-graph state with a code planner to succeed more often on non-Markovian robot tasks than standard VLA models.
arxiv:2604.22238 v2 · 2026-04-24 · cs.RO
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Claims
On real-world non-Markovian tasks, CodeGraphVLP improves task completion over strong VLA baselines and history-enabled variants while substantially lowering planning latency compared to VLM-in-the-loop planning.
The semantic-graph state can reliably maintain task-relevant entities and relations under partial observability in cluttered real environments, allowing the code planner to perform accurate progress checks.
CodeGraphVLP uses a semantic-graph state and executable code planner to enable reliable long-horizon non-Markovian robot manipulation, improving task success and lowering latency over standard VLA baselines.
Receipt and verification
| First computed | 2026-06-09T01:05:17.720712Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
7515a412ace32d6a71e2f07d72f5bd980de31fcdf62e3a0be06f543c595d9f07
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OUK2IEVM4MWWU4PC6B6XF5N5TA \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 7515a412ace32d6a71e2f07d72f5bd980de31fcdf62e3a0be06f543c595d9f07
Canonical record JSON
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